This is a cohesive and comprehensive book on statistical omics from a biopharmaceutical perspective which focuses on presenting statistical methods, including false discovery rate for analyzing omics data in biomedical research. It is enriched with practical examples in biopharmaceutical/biomedical research. The book is written for researchers who want to get involved in omics and data analysis in biomedical research as well as for Master/Ph.D. students who want training in omics and related data analysis.
Introduction to Statistical Omics. General Statistical Methods in Omics.
Multiplicity Issue and Statistical Solutions in Omics Data. Statistical
Epigenomics. Statistical Next-Generation Sequencing. Statistical Genome-Wide
Association Studies. Statistical Expression Profiling. Statistical
Metabolomics. Statistical Proteomics. Statistical High-Throughput Screening.
Statistical High-Content Screening. Data Mining in Omics. Bayesian Methods
for Next Generation Sequencing and Gwas Studies. Sensitivity and Specificity
Analysis in Omics.
